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10/13/2022
A Dual Control Variate for doubly stochastic optimization and black-box variational inference
In this paper, we aim at reducing the variance of doubly stochastic opti...
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09/28/2022
Score Modeling for Simulation-based Inference
Neural Posterior Estimation methods for simulation-based inference can b...
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08/16/2022
Langevin Diffusion Variational Inference
Many methods that build powerful variational distributions based on unad...
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03/08/2022
Variational Inference with Locally Enhanced Bounds for Hierarchical Models
Hierarchical models represent a challenging setting for inference algori...
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07/08/2021
MCMC Variational Inference via Uncorrected Hamiltonian Annealing
Given an unnormalized target distribution we want to obtain approximate ...
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05/13/2021
Empirical Evaluation of Biased Methods for Alpha Divergence Minimization
In this paper we empirically evaluate biased methods for alpha-divergenc...
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10/19/2020
On the Difficulty of Unbiased Alpha Divergence Minimization
Several approximate inference algorithms have been proposed to minimize ...
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07/29/2020
Approximation Based Variance Reduction for Reparameterization Gradients
Flexible variational distributions improve variational inference but are...
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11/05/2019
A Rule for Gradient Estimator Selection, with an Application to Variational Inference
Stochastic gradient descent (SGD) is the workhorse of modern machine lea...
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10/30/2018
Using Large Ensembles of Control Variates for Variational Inference
Variational inference is increasingly being addressed with stochastic op...
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06/25/2018